Value of data in acquired company?
August 07, 2024
by a searcher from Johns Hopkins University in Melbourne VIC, Australia
'Data ins the new oil', not a new saying but highlights that many companies we're looking to acquire across the community could be sitting on mountains of very valuable data.
How have you modelled data value into your investment thesis?
from University of Toronto in Toronto, ON, Canada
When we go away from the more data-saturated industries like eCommerce, and all of a sudden we're in a land of very little useful data collected, i.e. manufacturing or agriculture. Those industries weren't built around data collection, and for them collecting ANY information to analyze is a pain (whoever used SAP will confirm), and is usually VERY localized, i.e. speed of equipment or temperature in a fermentation tank that they actually need to run the machines. New, more automated factories are most likely better equipped in terms of data collection.
Personally, I would be wary of trying to define what value any particular company holds in its data, especially looking from outside as a searcher, unless it's something obvious like customer sales list or some proprietary manufacturing processes or product recipes that would most likely be considered IP, including trade secrets.
from INSEAD in Singapore
We work with startups and SMEs to get ROI from their data, and the most common archetype is one where management have high opinions of scope, accuracy, or potential of data, but it isn't supported by the reality on the ground. While I'm a dreamer about data being a part of an investment thesis/post-acquisition business model, you have to be able to execute from the starting point of the business, and the VAST majority of businesses are in a shitty state. Given these I would:
- value the data at zero and consider it only as upside to the investment case
- if DD access allows, try to talk to hands on operators to get a sense of how they make decisions
- become a customer of the business, see what information is captured in your interactions with it - look out for quality checks on ingestion (e.g., phone number validation, duplicate account detection)
Anecdotal ground level inputs will give you a better sense of relative maturity internally than any statement from the owners, a cultural value or similar top-down assessment
We've worked on both the data commercialisation angle for businesses and with data brokers who purchase this type of info so should be able to give you a decent lay of the land if you have more questions--drop me a connect on LinkedIn.